During a break in between offsite meetings that Edd and I were attending the other day, he asked me, “did you read the Barlow piece?”

“Umm, no.” I replied sheepishly. Insert a sidelong glance from Edd that said much without saying anything aloud. He’s really good at that.

In my utterly meager defense, Mike Loukides is the editor on Mike Barlow’s Real-Time Big Data Analytics: Emerging Architecture. As Loukides is one of the core drivers behind O’Reilly’s book publishing program and someone who I perceive to be an unofficial boss of my own choosing, I am not really inclined to worry about things that I really don’t need to worry about. Then I started getting not-so-subtle inquiries from additional people asking if I would consider reviewing the manuscript for the Strata community site. This resulted in me emailing Loukides for a copy and sitting in a local cafe on a Sunday afternoon to read through the manuscript.

Since I, ahem, hadn’t exactly been paying the closest attention to the history behind the piece, I wasn’t certain what to expect.

While I was reading through the manuscript and coming across points such as “for some, real-time big data analytics (RTBDA) is a ticket to improved sales, higher profits and lower marketing costs. To others, it signals the dawn of a new era in which machines begin to think and respond more like humans,” I realized that Barlow was providing distilled insight and context for managers looking to understand what “real-time” means and how it may impact the overall architecture of a data system.

In the data industry we often bandy about terms such as “real-time data analytics.” A lot. Yet, we often don’t pause to provide context around the ever evolving definition of “real-time.” Why? Well, likely because data innovations are moving at the speed of light and we may figure, “why worry about what we don’t have to?” Then, it may take something like a sidelong glance from a colleague to remind us that it isn’t about “worrying” per se … it is about being connected to the various stakeholders within our community.

In Real-Time Big Data Analytics: Emerging Architecture, Barlow takes the time to discuss what real-time means, what an architecture for a real-time data stack looks like, and what the different phases of real-time are. Also, as Barlow correctly reminds us, “focusing on the stakeholders and their needs is important because it reminds us that the RTBDA technology exists for a specific purpose: creating value from data.”